Study on Healthcare Security System-Integrated Internet of Things (IoT)

Introduction

Thanks to the abundance of IoT devices that are available in various locations and the enormous amounts of data and information they contain, Internet of Things (IoT) healthcare systems offer a solid foundation for smart sensor technology. Huge volumes of data are released by IoT-based healthcare systems, yet security and privacy are crucial concerns. IoT sensors and their released data can be supported by object and cloud network topologies. The Internet of Things (IoT) is a system of linked, intelligent sensors that can perceive their surroundings and share data and processes from many areas. It is utilised in a variety of industries, including smart transportation, finance, railroads, and healthcare. Different domains are involved with smart IoT-based sensors, particularly in smart healthcare systems. The majority are offered in stores. IoT infrastructure security design is crucial for a variety of technological, scientific, and commercial reasons, including privacy and security. Security concerns are governed by IoT architectures, technologies, and design approaches. The internet of things architecture is divided into layers, and each layer makes use of a different topology and piece of hardware to maintain sensor data standardisation, privacy protection, and parameter coordination(Polu, 2019).

To track and manage the healthcare system, IoT systems need a range of data and sensors. Wireless sensors are crucial for distant security, whereas vision-based sensors improve monitoring capacity. These sensors use the concept of physical position based and are vision-based. Home-based deployment of a wireless sensor for patient eyesight that is linked to an LPWAN base station and a cloud with machine learning capabilities (Toghuj & Turab, 2022).

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  Smart gadgets are those that can communicate with one another and are connected to a network or other devices. Since they only make up a minor portion of the notion, it is inaccurate to refer to them as IoT. It is preferable to refer to intelligent objects or intelligent things rather than merely devices. IoT may be used for basic calculations, communication, discovery, message reception and response (Janardhana et al., 2023; Reddy et al., 2023; Selvakumar et al., 2023). The ability to make anything intelligent is made possible by the fact that sensors are now more affordable, simple to install, and affordable than ever. They are not required for intelligent things, though.

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  Bluetooth, NFC, Wi-Fi, low-power wide-area networks, and LoRa are just a few examples of the smart objects that require wireless networks to communicate with one another.

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  RFID technology is a significant advancement over conventional barcodes because it makes it possible to create microchips for wireless data exchange. It has writing capabilities, requires no line-of-sight contact, and can read several tags simultaneously.

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  Big data from intelligent objects, such as temperature, pressure, altitude, motion, proximity to other objects, biometrics, sound, etc., must be combined and analysed using cloud computing. One of the main problems with IoT is the integration of all this data. A platform called cloud computing enables on-demand network access to computational resources. It receives data from intelligent devices, processes and interprets it, and then presents web-based visualisations. As a result, there will be a large market with lots of potential to add value for IoT application users. These data are analysed using machine learning techniques and big data analytics. Artificial intelligence known as machine learning enables computers to become smarter by learning from the data they are fed. The quantity of data produced by IoT applications necessitates a large increase in storage space, despite the fact that big data has been a hot issue. Big businesses utilise edge computing to pre-process data before sending it to the cloud.